Bringing a Feminist Curiosity to Monitoring, Evaluation, and Learning (MEL): Tracing Feminist, Postcolonial, and Development Theories in Feminist MEL
Bibliographic record
Abstract
Critical theories, specifically feminist, postcolonial, and development theories, inform and shape much of the practice of international development, by both criticising current conventions and procedures as well as introducing new ways of thinking. One current frontier within development practice involves reimagining Monitoring, Evaluation, and Learning (MEL) practices according to feminist principles, which is referred to as feminist MEL. However, in the context of feminist MEL, the connection between theory and practice is not always clear. This research aims to contribute to bridging the gap between theory and practice by exploring the case study of one organisation, the Women’s International League for Peace and Freedom (WILPF), and their early-stage development and conceptualisation of feminist MEL. More specifically, it aims to understand how their interpretation of feminist MEL practice draws from theory by analysing how feminist, postcolonial, and development theories are interpreted and presented within official documents and interviews of staff members from WILPF. The findings show that WILPF’s interpretation of MEL coherently draws inspiration from critical contributions to feminist, postcolonial and development like black and intersectional feminism, decolonial approaches, and ‘liberating’ perspectives on empowerment. These insights underscore the significant role of theory in shaping development practice, suggesting that an intimate, symbiotic relationship between theory and practice leads to more reflective and adaptive approaches. Additionally, they raise questions for further research on whether grounding practice in progressive theory can help resist cooptation and ‘rendering technical.’
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.140 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".